The User Guide is the primary resource documenting key concepts that will help you use HoloViews in your work. For newcomers, a gentle introduction to HoloViews can be found in our Getting Started guide and an overview of some interesting HoloViews examples can be found in our Gallery. If you are looking for a specific component (or wish to view the available range of primitives), see our Reference Gallery.
These user guides provide detailed explanation of some of the core concepts in HoloViews:
- Annotating your Data
Core concepts when annotating your data with semantic metadata.
- Composing Elements
Composing your data into layouts and overlays with the
- Applying Customizations
Using the options system to declare customizations.
- Style Mapping
Mapping your data to the visual attributes of your plot.
- Dimensioned Containers
Multi-dimensional containers for animating and faceting your data flexibly.
- Building Composite Objects
How to build and work with nested composite objects.
- Live Data
Lazily generate data on the fly and generate engaging interactive visualizations.
- Tabular Datasets
- Gridded Datasets
Explore gridded data (n-dimensional arrays) with NumPy and XArray.
- Geometry Data
Working with and representing geometry data such as lines, multi-lines, polygons, multi-polygons and contours.
- Indexing and Selecting Data
Select and index subsets of your data with HoloViews.
- Transforming Elements
Apply operations to your data that can be used to build data analysis pipelines
- Responding to Events
Allow your visualizations to respond to Python events using the ‘streams’ system.
- Custom Interactivity
Use Bokeh and ‘linked streams’ to directly interact with your visualizations.
- Data Processing Pipelines
Chain operations to build sophisticated, interactive and lazy data analysis pipelines.
- Creating interactive network graphs
Using the Graph element to display small and large networks interactively.
- Working with large data
Leverage Datashader to interactively explore millions or billions of datapoints.
- Working with Streaming Data
Demonstrates how to leverage the streamz library with HoloViews to work with streaming datasets.
- Creating interactive dashboards
Use external widget libraries to build custom, interactive dashboards.
These guides provide detail about specific additional features in HoloViews:
- Installing and Configuring HoloViews
Additional information about installation and configuration options.
- Customizing Plots
How to customize plots including their titles, axis labels, ranges, ticks and more.
Overview of colormaps available, including when and how to use each type.
- Plotting with Bokeh
Styling options and unique Bokeh features such as plot tools and using bokeh models directly.
- Deploying Bokeh Apps
Using bokeh server using scripts and notebooks.
- Link bokeh plots
Using Links to define custom interactions on a plot without a Python server
- Plotting with matplotlib
Styling options and unique Matplotlib features such as GIF/MP4 support.
- Plotting with plotly
Styling options and unique plotly features, focusing on 3D plotting.
- Working with renderers and plots
Plotclasses for access to the plotting machinery.
- Using linked brushing to cross-filter complex datasets
Explains how to use the link_selections helper to cross-filter multiple elements.
- Using Annotators to edit and label data
Explains how to use the annotate helper to edit and annotate elements with the help of drawing tools and editable tables.
- Exporting and Archiving
Archive both your data and visualization in scripts and notebooks.
- Continuous Coordinates
How continuous coordinates are handled, specifically focusing on
- Notebook Magics
IPython magics supported in Jupyter Notebooks.